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It’s the linchpin for identifying bottlenecks slowing development and draining your budget. Value Stream Management (VSM) solutions shine a light on these friction points, enabling leaders to identify areas needing improvement and take quick corrective action. VSM emerges as an indispensable asset.
Greschen walked through how to leverage a Value Stream Management (VSM) platform to create the flow models you need to get the metrics and data that will help you identify opportunities and make improvements. Watch Now Discovering how Spotify does product Title: How Do We Do Product at Spotify?
What if the principles that transformed softwaredevelopment over the last decade could be the key to successfully implementing AI in your organization? Patrick Debois is credited with coining the term “DevOps” and has been instrumental in shaping how organizations approach softwaredevelopment and operations.
Among other practices, they supported persistently funded, cross-functional teams led by product managers to iteratively deliver value. Fast-forward to today, when softwaredevelopment is part of every companys portfolio. These structures and practices are called the product operating model. What is a Product Operating Model?
The idea of cutting waste, a principle from manufacturing, is relevant more than ever in softwaredevelopment and knowledge work as a means to increase efficiency. This highlights the critical need for understanding where waste is coming from within the software delivery lifecycle and developing strategies to mitigate it.
It’s no surprise the abundance of moving parts contributes to an ever-ambiguous world for software delivery. With a multitude of products and services that companies serve to customers, the recognition of Value Stream Management (VSM) in modern software delivery has never been stronger.
The softwaredevelopment methodologies and organizational design principles harnessed by digital natives are well documented. The latest advances in generativeAI and Large Language Models (LLMs) have become ubiquitously available at an unprecedented rate.
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Identification is carried out through comprehensive testing, much like quality assurance in traditional softwaredevelopment. We test AI models using diversified datasets that reflect the real world’s complexity, making sure they work accurately and fairly across different scenarios and demographics.
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